The Datadog alternative for monitoring as code
Checkly runs API, browser, and heartbeat monitoring code-first, not click-first. Your checks are native Playwright, they live in the repo, and you run them locally before they ship.
Playwright-native No vendor lock-in Predictable pricing
Trusted to monitor mission-critical flows at teams like these
“The native Playwright integration, which you can configure as code, made things much easier.”
I just personally disliked [Datadog’s] test editor for UI synthetic tests. It was horrible to work with.
Built for how modern software is actually shipped
Built on open-source technologies, with no vendor lock-in. Your monitors are flexible, reviewable, and version-controlled like the rest of your stack, not locked inside a vendor’s UI.
Monitoring as code, end to end
Your monitors live in version control. You write them in TypeScript, review them in a pull request, and ship them in CI alongside the app. Datadog stores tests in its UI. Its monitoring-as-code story stops at a Terraform provider.
Built for engineering teams
Checkly runs where engineers already work. Write monitors on your local machine, verify preview deploys in CI, and watch production from the command line. No recorder, no separate portal to keep in sync after every release.
Synthetic monitoring is all we do
Every engineer we have works on API, browser, and heartbeat monitoring. It is the product, not one tab inside an observability suite competing with logs, APM, and RUM for the roadmap.
Checkly vs. Datadog
A focused, code-first synthetic monitoring platform against a synthetic module inside a broad APM suite. Here’s where the difference shows.
Native Playwright runtime
Monitoring as code
Local run and debug
Command line interface
API monitoring
Heartbeat monitoring
Status pages
Pricing model
● Full support·— Limited·✕ Not available
Where Datadog leads: full-stack APM and trace correlation, native mobile app testing, and built-in incident management and on-call. If those matter more than code-first synthetics, Datadog fits. If synthetic monitoring is the job, Checkly is built for it.
Monitor everything, not just what fits the budget
Datadog meters every test type on its own counter, so teams dial back frequency and coverage to keep the bill down. Checkly is one predictable plan, at a fraction of the per-run rate. Run every critical flow as often as it needs.
One plan. One run pool.
Up to 3.6× cheaper per run
A separate meter for each.
Costs compound with every location and frequency bump.
“There are some tests we schedule every 10 minutes, or even every hour, because it was too expensive to run them every five minutes in Datadog.”
From your IDE to production in three commands
Write checks in TypeScript, run them in CI, deploy them to production. The same workflow as the rest of your code, with the same tools.
Code your monitoring checks
Your app code lives in the repository. Your monitoring should too. Reuse the Playwright tests you already write and turn them into always-on production monitors. No duplication, no drift.
Test and verify locally or in CI
Run checks from your local machine or on every deploy in CI. They execute on Checkly’s global infrastructure, exactly as they will in production. Datadog runs cloud-only, so this step has no local equivalent.
Deploy for 24/7 monitoring
Deploy and version your monitoring from the command line, right alongside your application deploys. One command puts it live across 20+ locations.
Fit check
When should you choose Checkly over Datadog?
Checkly is a strong fit when
- Your developers want Playwright browser checks and API monitors in the same TypeScript workflow.
- You want monitors reviewed in Git, tested locally, and deployed through CI.
- You already have logs, metrics, or APM and need a focused outside-in reliability signal.
Checkly may not be the best fit when
- You want one vendor to collect infrastructure metrics, logs, traces, security, and synthetic checks.
- Your team prefers to configure every monitor in an operations UI instead of a code and pull-request workflow.
Key facts
Checkly at a glance
The facts a buyer usually has to dig for, in one place, each one traceable to the documentation it comes from.
- Category
Synthetic monitoring and continuous testing
Checkly is not an APM, a log aggregator, or a real user monitoring tool. It watches an application from the outside the way a customer does.
- Browser checks
Native Playwright, not a proprietary recorder
Browser checks and multi-file Playwright check suites run the same test code your team already runs in CI.
- Locations
22 public locations, plus private locations
Public locations span the Americas, EMEA, and Asia Pacific. Private locations run a lightweight agent inside your own network for internal services.
- Configuration
TypeScript, Terraform, or Pulumi
Monitors are defined in code, reviewed in pull requests, tested locally, and deployed from CI. No agent installation is required on your hosts.
Checkly monitoring as code docs (opens in a new tab)Checkly CLI docs (opens in a new tab)
- Failure investigation
OpenTelemetry traces, logs, and screenshots
A failing check links to the trace of the request it made, so a broken journey points at the service behind it.
- Where Datadog leads
Full-stack observability breadth
Infrastructure metrics, log management, APM, security, and incident management in one suite. Checkly does not replace those; check Datadog’s own docs and pricing for current scope.
Datadog Synthetics docs (opens in a new tab)Datadog pricing (opens in a new tab)
Facts checked . Vendor pricing and feature pages change without notice, so verify anything decision-critical against the linked source.
Decision criteria
How to evaluate Checkly against Datadog
Six questions that decide this comparison for most teams. Each one links to the documentation where you can check both products yourself.
Who owns a monitor
If monitors live in a console, the team that ships the change is rarely the team that updates the check, and coverage drifts behind the product.
How Checkly answers it: Monitors are TypeScript files in your repository, reviewed in the same pull request as the feature they cover and deployed by CI.
VerifyCheckly monitoring as code docs (opens in a new tab)Datadog Synthetics docs (opens in a new tab)
What the browser check actually runs
A recorder-based test is a second artefact to maintain. Reusing an existing suite is the difference between monitoring on day one and a rewrite project.
How Checkly answers it: Checkly runs Playwright directly, including multi-file check suites with fixtures and project configuration.
VerifyCheckly Playwright check suite docs (opens in a new tab)Datadog Synthetics docs (opens in a new tab)
How runs are metered
Per-test-type metering pushes teams to lower frequency and drop coverage, which is exactly the coverage that catches regressions.
How Checkly answers it: Browser, API, and heartbeat checks draw on one plan. Compare the per-run rate and the included volume against your real check count and frequency.
VerifyCheckly pricing (opens in a new tab)Datadog pricing (opens in a new tab)
Where a failure sends you next
Knowing a checkout flow broke is only useful if the next click narrows it to a service, a deploy, or a dependency.
How Checkly answers it: Failures carry the OpenTelemetry trace, console and network logs, and screenshots from the run that failed.
VerifyCheckly traces docs (opens in a new tab)Datadog Synthetics docs (opens in a new tab)
Breadth versus depth of the platform
Consolidating on one vendor has real value. It is only the wrong trade when the consolidated tool is weaker at the job you care most about.
How Checkly answers it: Checkly is deliberately scoped to outside-in synthetic monitoring and sits alongside whichever observability backend you already run.
VerifyCheckly synthetic monitoring docs (opens in a new tab)Datadog pricing (opens in a new tab)
Coverage of internal and non-HTTP services
Most estates have services that are not a public URL: internal APIs, brokers, DNS, and scheduled jobs that fail silently.
How Checkly answers it: URL, TCP, DNS, ICMP, gRPC, and heartbeat monitors cover those, and private locations reach services behind a firewall.
VerifyCheckly uptime monitoring docs (opens in a new tab)Checkly locations docs (opens in a new tab)
Criteria were drawn from the evaluation questions Checkly hears most often in Datadog migrations. Statements describe Checkly's behaviour only; Datadog capabilities and prices should be confirmed against Datadog's own documentation, which changes independently of this page. Last reviewed .
Need more proof? Listen to the engineers
“The Checkly CLI has enhanced our engineering team’s ability to quickly build, validate, and deploy an entire suite of checks from their local development environment.”
“We’ve been using Checkly for months and it’s been phenomenal. Super easy to set up, works flawlessly and intuitively. The team is super receptive and quick to help.”
“Checkly is a fabulous developer tool. The flexible features and developer-friendly API made the integration super easy, and their support is friendly and knowledgeable.”
“Checkly is incredible: it combines Pingdom, Ghost Inspector, and Assertible in the same app, and the insights are much more detailed.”
“A real advantage Checkly gives us is that we’re not waiting for users to report an issue, or waiting on a staff member to file a ticket. Checkly gives us real-time feedback on what is and isn’t working.”
Coming from Datadog?
See the Migrator in action. We'll show you how your Datadog Synthetics tests become version-controlled Checkly monitors, and exactly what you'll save.
We map your Datadog Synthetics tests
Show us your existing browser and API tests. We translate them into Checkly constructs and native Playwright specs that live in your repo.
You see the cost delta before you commit
We take your current run volume, locations, and frequency, and put a real number next to what the same coverage costs on Checkly.
Your first monitors go live with us
A guided session with our team to get checks running in CI and deployed to production, not a slide deck.